Since we can’t travel billions of years back in time not yet, anyway one of the best ways to understand how our universe evolved is to create computer simulations of the process using what we do know about it.
Most of those simulations fall into one of two categories: slow and more accurate, or fast and less accurate. But now, an international team of researchers has built an AI Services that can quickly generate highly-accurate, three-dimensional simulations of the universe even when they tweak parameters the system wasn’t trained on.
“It’s like teaching image recognition software with lots of pictures of cats and dogs, but then it’s able to recognize elephants,” researcher Shirley Ho said in a press release. “Nobody knows how it does this, and it’s a great mystery to be solved.”
The scientists Explained in a detailed way how they created this universe simulator, which they’ve named the Deep Density Displacement Model (D3M), in a study published in the journal Proceedings of the National Academy of Sciences.
The goal was to teach D3M how to model the way gravity shapes the universe. To that end, they started by feeding the system 8,000 different gravity-focused simulations created by a highly accurate existing universe simulator.
That system needed 300 computation hours to create just one of its simulations, but after training on the data, D3M was able to produce its simulations of a cube universe 600 million light-years across in just 30 milliseconds. Those simulations were more accurate than those of the existing “fast” systems, which need a couple of minutes to create a simulation.
But speed isn’t the most remarkable thing about D3M.
That would be its ability to accurately simulate what the universe would look like even if the researchers changed parameters that weren’t included in its training data. For example, they could tweak the percent of dark matter in their universe, and D3M could accurately simulate that universe’s evolution.
In addition to helping physicists like how better to understand the universe’s evolution, this strange behavior has the potential to help computer scientists better understand AI.
“We can be an interesting playground for a machine learner to use to see why this model extrapolates so well, why it extrapolates to elephants instead of just recognizing cats and dogs. “It’s a two-way street between science and deep learning.”
Artificial intelligence changing the rhythm of satellite communication
Nowadays, artificial intelligence has become a popular phenomenon in automation. If we talk about satellite communication, we know that maintaining a satellite every time is a big thing, because security, data, and information are carried by the satellite and it is major harm in the world. At any time, the satellite could be attacked, or even in its basement. What does the situation look like for ongoing missions? What facilities need to be a high priority to take action and protect? Specific algorithms to compensate for those situations must include some technology that identifies problems based on past, present, and future approaches, and if taken into account, it will take immediate action. We know we cannot automate the whole thing, but some things can be controlled by artificial intelligence.
Real-time satellite communication decisions and seamless satellite control are difficult to manage and change the space environment are prevented from proper satellite communication, which is now operated by NASA. The recent development of cognitive technology is new excitement in the construction of satellite communications systems. If we talk about satellite broadcasts, Wide Network Solutions is a leading provider of advanced satellite communication systems with fiber optic transmission, satellite monitoring services and more.
NASA has introduced Cognitive Radio, an intelligent and adaptive network technology that can detect available channels wirelessly and modify broadcast parameters to simultaneously run most communications and improve radio operating behavior. For NASA, the space environment presents complex challenges that can reduce cognitive radio. NASA Principal Investigator Janet C. Klein on the Cognitive-Communication Project at the Glenn Research Center in Cleveland, Ohio. By applying artificial intelligence and machine learning, satellites control these systems smoothly, making real-time decisions without waiting for instruction. “
According to AI researchers, astronomers have more foresight, and machine learning algorithms can more quickly detect debris that comets leave in their wake. If we accelerate the meteor’s analysis, we can detect distant orbits, but these are dangerous comets. NASA has sponsored this artificial intelligence pilot research program. NASA is working with defense and machine learning researchers. So, it helps with space operations as well as reinforces security parameters for defense.
To implement AI-based technology in space communications, many tests are underway and various projects are underway. Researchers are also predicting drone handicrafts that can fly to the exoplanets. But, for that matter, handicrafts can endure years of solitary travel and can cope with and respond to ever-changing, extremely unpredictable conditions. From temperature differences to cosmic objects.
Research is also underway to predict solar storms by using AI tools to analyze data from the Solar Dynamics Observatory. After finding the relationships between the corona and magnetic activity in the photosphere, we can determine the coronal mass ejections and the cause of the flare. There are many more projects going on and we are sure the revolution will come very soon. Artificial intelligence, cognitive automation, and machine learning enhance the way we deal with satellite communication and space technology.
The NASA spacecraft usually relies on human-controlled radio systems to communicate with the Earth. As space data collection grows, NASA Cognitive Radio will incorporate artificial intelligence into space communications networks, meet demand and increase efficiency.
“Modern space communications systems use sophisticated software to support science and exploration,” said Janet C. Klein, lead researcher at the Cognitive-Communication Project at NASA’s Glenn Research Center in Cleveland, Ohio. Said Briones. “By applying artificial intelligence and machine learning, satellites control these systems smoothly, making real-time decisions without waiting for instruction.”
To understand cognitive radio, it is easy to get started with land-based applications. U.S. In, the Federal Communications Commission (FCC) allocates parts of the electromagnetic spectrum used for communications to various customers. For example, the FCC allocates spectrum to cell service, satellite radio, Bluetooth, Wi-Fi, and more. The spectrum is divided into a limited number of taps connected to the water main.
What happens when there are no faucets left in the faucet? How does the device access the electromagnetic spectrum when all the taps are taken?
Software-defined radios such as Cognitive Radio use artificial intelligence to use the lower parts of the electromagnetic spectrum without human intervention. These “white spaces” are currently unused but already licensed, of the spectrum. The FCC allows a cognitive radio to use its primary user’s unused frequency until the user is reactivated.
In terms of our metaphorical watering hole, cognitive radio draws on the water that is wasted. Cognitive radio can use most of the “faucet” regardless of the frequency of the “faucet.” Cognitive radio shifts from one white spot to another, using electromagnetic spigots when they become available.
“The recent development of cognitive technology is new excitement in the construction of communication systems,” says Briones. “We see these technologies make our communication networks more in-depth and resilient for missions exploring the depths of space.